Identifying Predictors for Pertussis Disease in Texas Infants Utilizing Surveillance and Birth Certi

1
Identifying Predictors for Pertussis Disease in
Texas Infants Utilizing Surveillance and Birth
Certificate Data from 1999-2003

• Lucille Palenapa
• IDEW Presentation
• Fri, Jun 27, 2008

2
Overview

• Review project
• Objective
• Methodology
• Results
• Recommendations
• QA

3
Pertussis Challenges

• Difficult to diagnose distinguish
• Often ruled out based on vaccine history
• Lab results often not reliable
• Difficult to obtain sterile sample
• Need to facilitate earlier identification of
  disease
• Establish risk factors for pertussis disease

4
Texas Birth Certificate Data

• Utilized in past research to assess risk factors
  for infectious diseases
• Comprehensive source of infant, maternal and
  paternal characteristic data

5
Objective

• Identify significant risk factors for pertussis
  disease in infants lt12 months of age in Texas
  utilizing surveillance and birth certificate data
  from 1999-2003

6
Methodology

• Case-infant defined
• Infant reported to DSHS as a confirmed or
  probable pertussis case
• lt12 months at onset
• Born in Texas from 1999-2003
• Control-infant defined
• Randomly selected by same date of birth as
  case-infant
• Not reported as pertussis case to DSHS
• Born in Texas from 1999-2003

7
Exclusion criteria

• Infants who were
• Ruled out or lost to follow-up
• Not born in Texas
• gt12 months at disease onset
• gt 1 case of pertussis in 5-year study (counted
  only once)

8
Methodology

• Retrospective case-control study
• 5 year data (1999-2003)
• DSHS pertussis surveillance data
• Control group
• Texas birth certificate data
• DSHS IRB submission

9
Methodology (Data Collection)

• After IRB approval, collected
• Surveillance Data
• Identified infants reported to DSHS as (confirmed
  and probable) pertussis cases who were lt12 months
  at onset for each respective year (1999-2003)
• Birth certificate data
• Received large birth data files (avg 300-365K
  records w/ avg 200 fields /year)

10
Methodology (cont.)

• SAS Statistical Software Utilized
• Recode and reformat birth certificate data into
  readable format
• Match cases to birth certificate data
• Matched on name and date of birth
• Quality assurance done by hand to ensure match of
  surveillance case to birth data
• 451 cases
• 3 controls randomly selected for each case based
  on same date of birth
• 1353 controls

11
Methodology (cont.)

• 15 variables initially chosen for analysis
• 2 variables (birth length medicaid
  participation) eliminated because data
  completeness lt50
• Variables chosen based on indications of
  biological feasibility and on previous
  epidemiological studies

12
Table 1. Variables Selected for Analysis from
Texas Birth Certificate

• Variable missing Selected
• (Yes/No)
• (Infant Charac.)
• Birth length 51.2 No
• Birth sequence 0.0 Yes
• Birth type 0.0 Yes
• Birth weight 0.1 Yes
• Gestational age 1.9 Yes
• No. siblings living 0.3 Yes
• Sex 0.0 Yes

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Table 1. Variables Selected for Analysis from
Texas Birth Certificate (cont.)
Variable missing Selected (Yes/No) (Ma
ternal Charac.) Age 0.0 Yes Alcohol
Use 0.1 Yes Education 2.2 Yes
Hispanic Origin 0.4 Yes Marital
Status 0.2 Yes Medicaid 64.9 No
Prenatal Care 4.9 Yes Tobacco Use 0.7 Yes
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Analysis

• Descriptive statistics
• Multivariate logistic regression model
• Reducing confounders
• 10 odds ratio analyses, removal of variables not
  causing at least 10 change in OR

15

• Results

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Table 2. Mean Values of Continuous Variables
Describing Infant and Maternal Characteristics
by Case Status
Variable Case Control n451 n1353 Inf
ant Charac. Birth weight (gms) 3182.6 3306.7
Gestational age (wks) 40.1 39.4 No.
siblings living 1.5 2.1 Maternal Charac.
Age (yrs) 24.8 26.4 Education
(yrs) 13.7 14.1
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Table 3. Distribution of Categorical Variables
Describing Maternal Characteristics by Case Status
Variable Case Control n451 n1353 Doe
s mother use alcohol? Yes 5 (1.1) 8
(0.6) No 445 (98.9) 1334 (99.4)
Education gt12 yrs 188 (42.7) 414
(31.3) lt12 252 (57.2) 911 (68.8) Is mother
of Hispanic origin? Yes 242 (54.0) 640
(47.4) No 206 (45.9) 709 (52.6) Maternal
Status (Mother married?) Yes 277 (61.4) 932
(69.0) No 174 (38.6) 418 (30.9)
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Table 3. Distribution of Categorical Variables
Describing Maternal Characteristics by Case
Status (cont.)
Variable Case Control n451 n1353 Num
ber of prenatal visits gt1 420 (97.9) 1264
(98.2) 0 9 (2.1) 23 (1.8) Mothers
Race White 399 (88.5) 1160
(85.8) Black 41 (9.1) 146 (10.8) Native-Ame
rican 1 (0.2) 1 (0.1) Asian 9 (2.0) 39
(2.9) Pacific Islander 0 (0.0) 4
(0.3) Unknown 1 (0.2) 3 (0.2) Does mother
smoke cigarettes? Yes 42 (9.3) 70
(5.2) No 408 (90.7) 1271 (94.8)
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Table 4. Crude Odds Ratios and 95 Confidence
Intervals for Infant Pertussis According to
Maternal Characteristics
Variable Case Control
Effect n451 n1353 OR (95 CI)
Maternal age (yrs) lt19 103 178 2.3
(1.6-3.1) 20-29 238 749 1.2
(0.9-1.6) 30-39 103 401 Referent gt40 7 25
1.1 (0.5-2.6) Maternal education
(yrs) lt8 48 125 2.1 (1.3-3.3) gt8 and
lt12 280 698 2.2 (1.6-3.0) gt12 and
lt15 60 219 1.5 (0.9-2.2) gt16 52 283 Referen
t Is mother of Hispanic origin? Yes 242 640 1
.3 (1.1-1.6) No 206 709 Referent
20
Table 4. Crude Odds Ratios and 95 Confidence
Intervals for Infant Pertussis According to
Maternal Characteristics (cont.)
Variable Case Control
Effect n451 n1353 OR (95 CI)
Mother married Yes 277 932 Referent No 1
74 418 1.4 (1.1-1.7) Does mother
smoke cigarettes? Yes 42 70 1.9
(1.3-2.8) No 408 1341 Referent
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Table 5. Crude Odds Ratios and 95 Confidence
Intervals for Infant Characteristics
Variable Case Control
Effect n451 n1353 OR (95 CI)
Infant birth sequence 1st
426 1320 Referent gt2nd 25 33 2.3
(1.4-4.0) Infant birth type Single
426 1320 Referent Multiple 25 33 2.4
(1.4-4.0) Infant birth weight (gms) lt1499
8 22 1.2 (0.5-2.7) 1500-2499 50 61 2.7
(1.8-3.9) gt2500 393 1270 Referent
22
Table 5. Crude Odds Ratios and 95 Confidence
Intervals for Infant Characteristics (cont.)
Variable Case Control
Effect n451 n1353 OR (95 CI)
Infant gestational age (wks) lt37
110 245 1.5 (1.2-1.9) gt38
327 1087 Referent Infant sex Male
218 710 Referent Female 233 643 1.2
(0.9-1.9) No. of siblings living 0
146 526 Referent 1-4 290 787 1.3
(1.1-1.7) gt5 14 23 2.2 (1.4-4.4)
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Final Data Analyses

• Multivariate logistic regression
• 6 variables selected as significant predictors of
  pertussis disease
• 10 adjusted odds ratio
• No variable eliminated
• 6 variables still remained

24
Table 6. Crude Odds and Adjusted Ratios and 95
Confidence Intervals of Significant Predictors
for Pertussis
Variable Case Control Effect Adj.
Effect n451 n1353 OR (95 CI)
OR (95 CI) Infant birth type Single
422 1290 Referent Referent Multiple
25 33 2.4 (1.4-4.0) 1.9
(1.0-3.4) Infant birth weight lt1499 8
20 1.2 (0.5-2.7) 1.4 (0.6-3.4) 1500-2499
48 60 2.7 (1.8-3.9) 2.1
(1.4-3.3) gt2500 391
1243 Referent Referent No. of siblings
living 0 144 520 Referent Referen
t 1-4 289 780 1.3 (1.1-1.7) 1.8
(1.4-2.3) gt5 14 23 2.2
(1.4-4.4) 3.1 (1.5-6.5)
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Table 6. Crude Odds and Adjusted Ratios and 95
Confidence Intervals of Significant Predictors
for Pertussis (cont.)
Variable Case Control Effect Adj.
Effect n451 n1353 OR (95 CI)
OR (95 CI) Maternal cigarette use Yes
42 70 1.9 (1.3-2.8) 2.1
(1.3-3.5) No 405
1253 Referent Referent Maternal age lt19
101 175 2.3 (1.6-3.1) 3.0
(2.1-4.4) 20-29 237 734 1.2
(0.9-1.6) 1.3 (1.0-1.7) 30-39 102
390 Referent Referent gt40 7
24 1.1 (0.5-2.6) 1.0 (0.4-2.5) Maternal
Hispanic Origin Yes 242 628 1.3
(1.1-1.6) 1.3 (1.0-1.5) No
205 695 Referent Referent
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Significant Predictor Variables

• Variable Adj. OR (95 CI)
• -Number of siblings gt5 3.1 (1.5-6.5)
• -Maternal age lt19 yrs 3.0 (2.1-4.4)
• -Infant low birth weight
• (1500-2499 gms) 2.1 (1.4-3.3)
• -Maternal cigarette use
• (Yes) 2.1 (1.3-3.5)

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• Discussion Recommendations

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Number of siblings living

• No current literature w/ exact findings
• Similar findings
• As no. of older siblings increased, delay in
  immunization increased for household infants and
  younger siblings (Reading, Surridge, Adamson,
  2004)
• Infants from larger household size less likely to
  be fully immunized, more likely to have delayed
  immunization (Li Taylor, 1993 Peckham,
  Bedford, Senturia, Ades, 1989)
• Later born siblings more likely to have delayed
  immunization than firstborn children (Higgins,
  1990 Kaplan, Macie-Taylor, Boldsen, 1992
  Schaffer Szilagyi, 1995)
• Later born children more prone to infectious
  disease (Kaplan, 1990)

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Significant Maternal Variables

• Maternal Age
• Similar findings for young maternal age (Izurieta
  et al., 1996)
• Adolescent aged mothers found to have
  significantly lower levels of antibodies for
  pertussis than older mothers (Gonik, 2005
  Healy, 2006)

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Significant Infant Predictors

• Low birth weight (LBW) infant
• Biologically feasible
• Similar findings, LBW infants more likely to
  develop pertussis than normal birth weight
  infants (Langkamp Davis, 1996)

31
Maternal Cigarette Use

• Similar findings established
• Maternal smoking increases the likelihood of
  respiratory infections in infants (Ahmer et al.,
  1999 Ahmer, et al., 1998 Geng, Savage,
  Razani-Boroujerdi Sopori, 1996 Saadi, et al.,
  1996 Stocks Dezateux, 2003)
• Smoking during pregnancy assoc w/ several adverse
  outcomes
• Premature delivery
• Spontaneous abortion
• Growth restriction
• Increased risk of SIDS

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Limitations of Study

• Difficult to gauge the effects of many covariates
  with the statistical procedures used
• Problem of multiple comparisons present,
  acceptance criterion may have been satisfied
  purely by chance
• Use of birth certificate data to predict health
  outcomes has had mixed reviews
• Method for reporting disease

33
Recommendations

• Increase awareness and knowledge of serious
  dangers of pertussis
• Specially targeted education campaigns should
  include a focus on
• Infant households with large number of siblings
• Teen mothers
• Low birth weight infants
• Pregnant mothers and mothers with infants who
  smoke

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Recommendations (cont.)

• Cocooning strategy
• Immunization of family members and close
  contacts of the newborn
• Post-partum

• Keep infants up-to-date on vaccinations
• Tdap booster vaccine for adolescents and adults

35
Benefits of Study

• Aid clinicians by establishing risk factors to
  facilitate earlier recognition of disease and
  earlier consequent prophylaxis treatment of
  patient and close contacts
• Reduce health care costs associated with
  pertussis
• Reduce lost productivity

36
Benefits of Study (cont.)

• Protect those most vulnerable, the future of
  Texas

37
Study Contributors

• Rita Espinoza
• Marilyn Felkner
• Richard Taylor
• Eric Miller
• THANK YOU!
• Lucille Palenapa
• [phone] x.6611
• lucille.palenapa_at_dshs.state.tx.us